M. Anila

536 total citations
11 papers, 45 citations indexed

About

M. Anila is a scholar working on Plant Science, Cell Biology and Genetics. According to data from OpenAlex, M. Anila has authored 11 papers receiving a total of 45 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Plant Science, 3 papers in Cell Biology and 2 papers in Genetics. Recurrent topics in M. Anila's work include Rice Cultivation and Yield Improvement (6 papers), Plant Pathogenic Bacteria Studies (4 papers) and Plant-Microbe Interactions and Immunity (3 papers). M. Anila is often cited by papers focused on Rice Cultivation and Yield Improvement (6 papers), Plant Pathogenic Bacteria Studies (4 papers) and Plant-Microbe Interactions and Immunity (3 papers). M. Anila collaborates with scholars based in India. M. Anila's co-authors include G. Rekha, G. Harika, R. M. Sundaram, C. H. Balachiranjeevi, G. S. Laha, S. M. Balachandran, K. Pranathi, S. Bhaskar, M. B. V. N. Kousik and Yugander Arra and has published in prestigious journals such as PLoS ONE, 3 Biotech and Rice Science.

In The Last Decade

M. Anila

6 papers receiving 45 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. Anila India	3	44	7	4	3	1	11	45
K. Pranathi India	3	38 0.9×	11 1.6×	6 1.5×	3 1.0×	1 1.0×	7	44
Ya-Chih Hsueh Canada	3	28 0.6×	7 1.0×	3 0.8×	5 1.7×		3	32
Haicheng Liao China	2	47 1.1×	15 2.1×	4 1.0×	4 1.3×		4	55
M. B. V. N. Kousik India	3	37 0.8×	6 0.9×	5 1.3×	2 0.7×	2 2.0×	8	39
Suruchi Jindal India	5	50 1.1×	14 2.0×	7 1.8×	3 1.0×		8	60
María-Eugenia Ordoñez United States	2	36 0.8×	19 2.7×	5 1.3×	4 1.3×		2	37
Gwenaëlle Marchand France	3	32 0.7×	16 2.3×	4 1.0×	2 0.7×		3	41
Haiyang Wu China	2	63 1.4×	8 1.1×	2 0.5×	3 1.0×		3	69
Xunxiao Zhang China	2	18 0.4×	13 1.9×	6 1.5×	3 1.0×		2	26
Peter Aspesi Switzerland	1	41 0.9×	8 1.1×	2 0.5×	5 1.7×		2	45

Countries citing papers authored by M. Anila

Since Specialization

Citations

This map shows the geographic impact of M. Anila's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Anila with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Anila more than expected).

Fields of papers citing papers by M. Anila

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Anila. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Anila. The network helps show where M. Anila may publish in the future.

Co-authorship network of co-authors of M. Anila

This figure shows the co-authorship network connecting the top 25 collaborators of M. Anila. A scholar is included among the top collaborators of M. Anila based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Anila. M. Anila is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Rekha, G., M. S. Prasad, M. Sheshu Madhav, et al.. (2023). Identification and validation of blast resistance Pi1 gene in the derived mapping population of rice variety, NLR34449 through molecular markers. Indian Phytopathology. 76(4). 1091–1097.

2.

Rekha, G., G. Harika, M. Anila, et al.. (2022). Marker assisted pedigree breeding based improvement of the Indian mega variety of rice MTU1010 for resistance against bacterial blight and blast and tolerance to low soil phosphorus. PLoS ONE. 17(1). e0260535–e0260535. 6 indexed citations

3.

Anila, M., et al.. (2022). Evaluation of Rice Recombinant Inbred Lines Developed from the Cross Rasi × Improved Samba Mahsuri for Drought Tolerance. International Journal of Environment and Climate Change. 1537–1546.

4.

Ulaganathan, Kandasamy, Divya Balakrishnan, A. S. Hari Prasad, et al.. (2021). Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population. 3 Biotech. 11(12). 513–513. 4 indexed citations

5.

Hajira, S. K., M. Anila, G. Rekha, et al.. (2021). Identification of novel sources of resistance against bacterial blight disease through intensive screening of wild rice introgression lines. 49(2).

6.

Anila, M., et al.. (2019). Effect of drip fertigated and soil drenched liquid organic manures on productivity and quality of tomato.. 37(2). 495–499.

7.

Rekha, G., et al.. (2018). Screening of breeding lines of Improved Samba Mahsuri possessing Saltol QTL for seedling stage salinity tolerance. Journal of Pharmacognosy and Phytochemistry. 7(4). 1182–1185. 2 indexed citations

8.

Hajira, S. K., R. M. Sundaram, G. S. Laha, et al.. (2016). A Single-Tube, Functional Marker-Based Multiplex PCR Assay for Simultaneous Detection of Major Bacterial Blight Resistance Genes Xa21, xa13 and xa5 in Rice. Rice Science. 23(3). 144–151. 30 indexed citations

9.

Pranathi, K., et al.. (2016). A single-tube, functional marker-based multiplex PCR assay for simultaneous detection of major bacterial blight resistance genes in rice, Xa21, xa13 and xa5. 2 indexed citations

10.

Anila, M., et al.. (2016). Soil amelioration for rice productivity enhancement in lateritic soil. 53(2). 213–216. 1 indexed citations

11.

Rekha, G., et al.. (2015). Marker-assisted introgression of genes conferring resistance against bacterial blight & blast into RPHR-1005, the elite restorer line of the popular rice hybrid, DRRH-3.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact